Analysis of second outbreak of COVID-19 after relaxation of control measures in India

Impact of COVID-19 on Dental Practices in El Salvador and Mexico: A Comprehensive Survey Analysis

BACKGROUND AND OBJECTIVES

This study aimed to identify the relationship between prevention measures and protective barriers in dental practice in El Salvador and Mexico during the COVID-19 pandemic in 2020 and 2021.

MATERIALS AND METHODS

A longitudinal study was conducted from June 2020 to December 2021, involving 1,719 dentists divided into four groups based on location and year. A 20-question survey in Spanish was utilized and validated with a Cronbach's alpha value of 0.84.

RESULTS

The use of phone triage (OR = 1.3), thermometers (OR = 1.4), physical distancing (OR = 1.7), and face shields (OR = 2.6) was significantly associated with dental practice in both countries during the pandemic.

CONCLUSIONS

During 2020 and 2021, dental care in El Salvador and Mexico was significantly linked to COVID-19 preventive measures. Phone triage, thermometers, distancing, and face shields positively correlated with dental services. National health agencies should promote the use of minimum preventive measures in dental care, preparing for potential reinfections or new pandemics from emerging virus variants.

Impact of COVID-19 on mode choice behavior: A case study for Dhaka, Bangladesh

To ensure safety against the COVID-19, along with all other countries, Bangladesh as a least-developed country needs to deal with the changes in travel behavior, particularly changes in mode choice behavior. As Dhaka has been marked as a hotspot for the virus contagion, this paper has focused on the changes in mode choice behavior of Dhaka people due to the COVID-19 pandemic while they are on the road. A web-based questionnaire survey was conducted to capture the information on mode preferences and perspectives on travel characteristics for commute and discretionary trips before and during COVID-19. Multinomial Logit (MNL) model based on a utility function has been used to investigate the significance of the socio-demographic attributes and travel characteristics of the trips on the mode choice behavior and to calculate the maximum utility of the mode choice. This study highlighted some noticeable changes in perspective towards mode choice. People prefer walking, private cars, and rickshaw more during the pandemic as they feel these modes are more reliable, available, and cost-effective in this crucial time. Usage of public transportation dropped drastically for discretionary purposes. Additionally, usage of the on-demand vehicle increased during the pandemic as a large portion of commuters shifted to on-demand vehicles from public transportation. Furthermore, this paper suggested some viable policy-making implications to cope with the current pandemic and relatable future national and global crises. Finally, the paper concludes by suggesting some future research insights.

Oscillatory properties of class C notifiable infectious diseases in China from 2009 to 2021

Background

Epidemics of infectious diseases have a great negative impact on people's daily life. How it changes over time and what kind of laws it obeys are important questions that researchers are always interested in. Among the characteristics of infectious diseases, the phenomenon of recrudescence is undoubtedly of great concern. Understanding the mechanisms of the outbreak cycle of infectious diseases could be conducive for public health policies to the government.

Method

In this study, we collected time-series data for nine class C notifiable infectious diseases from 2009 to 2021 using public datasets from the National Health Commission of China. Oscillatory power of each infectious disease was captured using the method of the power spectrum analysis.

Results

We found that all the nine class C diseases have strong oscillations, which could be divided into three categories according to their oscillatory frequencies each year. Then, we calculated the oscillation power and the average number of infected cases of all nine diseases in the first 6 years (2009-2015) and the next 6 years (2015-2021) since the update of the surveillance system. The change of oscillation power is positively correlated to the change in the number of infected cases. Moreover, the diseases that break out in summer are more selective than those in winter.

Conclusion

Our results enable us to better understand the oscillation characteristics of class C infectious diseases and provide guidance and suggestions for the government's prevention and control policies.

A multicompartment mathematical model to study the dynamic behaviour of COVID-19 using vaccination as control parameter

To analyse novel coronavirus disease (COVID-19) transmission in India, this article provides an extended SEIR multicompartment model using vaccination as a control parameter. The model considers eight classes of infection: susceptible ( S ), vaccinated ( V ), exposed ( E ), asymptomatic infected ( A ), symptomatic infected ( I ), isolated ( J ), hospitalised ( H ), recovered ( R ). To begin, a mathematical study is performed to demonstrate the suggested model's uniform boundedness, epidemic equilibrium, and basic reproduction number. The findings indicate that if, R 0 < 1 , the disease-free equilibrium is locally asymptotically stable; but, if, R 0 > 1 the equilibrium is unstable. Secondly, we examine the effect on those who have received vaccinations with what are deemed optimal values. The suggested model is numerically simulated using MATLAB 14.0, and the results confirm the capacity of the proposed model to provide an accurate forecast of the progress of the epidemic in India. Finally, we examine the impact of immunisation on COVID-19 dissemination.

Modeling and staged assessments of the controllability of spread for repeated outbreaks of COVID-19

SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) has been causing an outbreak of a new type of pneumonia globally, and repeated outbreaks have already appeared. Among the studies on the spread of the COVID-19, few studies have investigated the repeated outbreaks in stages, and the quantitative condition of a controllable spread has not been revealed. In this paper, a brief compartmental model is developed. The effective reproduction number (ERN) of the model is interpreted by the ratio of net newly infectious individuals to net isolation infections to assess the controllability of the spread of COVID-19. It is found that the value of the ERN at the inflection point of the pandemic is equal to one. The effectiveness of the quarantine, even the treatment, is parametrized in various stages with Gompertz functions to increase modeling accuracy. The impacts of the vaccinations are discussed by adding a vaccinated compartment. The results show that the sufficient vaccinations can make the inflection point appear early and significantly reduce subsequent increases in newly confirmed cases. The analysis of the ERNs of COVID-19 in the United States, Spain, France, and Peru confirms that the condition of a repeated outbreak is to relax or lift the interventions related to isolation and quarantine interventions to a level where the ERN is greater than one.

Non-pharmaceutical interventions in a generalized model of interactive dynamics between COVID-19 and the economy

We use a simple general model of interactive dynamics between the COVID-19 pandemic and the economy to examine the impact of various non-pharmaceutical interventions in the form of restrictions on socio-economic activities like lockdowns, travel restrictions, etc. We mathematically demonstrate that these restrictions might be useful in preventing repeated waves of infection recurrence in the pandemic. These results are general and not dependent on choice of specific functional forms or parameter configurations. We set out briefly the implications of these results for public health interventions.

Numerical simulation and stability analysis of a novel reaction-diffusion COVID-19 model

In this study, a novel reaction-diffusion model for the spread of the new coronavirus (COVID-19) is investigated. The model is a spatial extension of the recent COVID-19 SEIR model with nonlinear incidence rates by taking into account the effects of random movements of individuals from different compartments in their environments. The equilibrium points of the new system are found for both diffusive and non-diffusive models, where a detailed stability analysis is conducted for them. Moreover, the stability regions in the space of parameters are attained for each equilibrium point for both cases of the model and the effects of parameters are explored. A numerical verification for the proposed model using a finite difference-based method is illustrated along with their consistency, stability and proving the positivity of the acquired solutions. The obtained results reveal that the random motion of individuals has significant impact on the observed dynamics and steady-state stability of the spread of the virus which helps in presenting some strategies for the better control of it.

Impacts of the COVID-19 Pandemic on Active Travel Mode Choice in Bangladesh: A Study from the Perspective of Sustainability and New Normal Situation

The COVID-19 pandemic has caused incredible impacts on people’s travel behavior. Recent studies suggest that while the demand for public transport has decreased due to passengers’ inability to maintain physical distance inside this mode, the demand for private automobile and active transport modes (walking and cycling) has increased during the pandemic. Policymakers should take this opportunity given by the pandemic and encourage people to use active transport more in the new normal situation to achieve sustainable transportation outcomes. This study explores the expected change in active transport mode usage in the new normal situation in Bangladesh based on the data from a questionnaire survey. The study finds that 56% and 45% of the respondents were expected to increase travel by walking and cycling, respectively, during the new normal situation. On the other hand, 19% of the respondents were expected to do the opposite. The study further identifies the factors influencing the expected change in travel by active transport modes during the new normal situation by developing multinomial logistic regression models. Finally, this study proposes policies to increase active transport use beyond the pandemic and ensure sustainable mobility for city dwellers and their well-being.

Enlightenment on oscillatory properties of 23 class B notifiable infectious diseases in the mainland of China from 2004 to 2020

A variety of infectious diseases occur in mainland China every year. Cyclic oscillation is a widespread attribute of most viral human infections. Understanding the outbreak cycle of infectious diseases can be conducive for public health management and disease surveillance. In this study, we collected time-series data for 23 class B notifiable infectious diseases from 2004 to 2020 using public datasets from the National Health Commission of China. Oscillatory properties were explored using power spectrum analysis. We found that the 23 class B diseases from the dataset have obvious oscillatory patterns (seasonal or sporadic), which could be divided into three categories according to their oscillatory power in different frequencies each year. These diseases were found to have different preferred outbreak months and infection selectivity. Diseases that break out in autumn and winter are more selective. Furthermore, we calculated the oscillation power and the average number of infected cases of all 23 diseases in the first eight years (2004 to 2012) and the next eight years (2012 to 2020) since the update of the surveillance system. A strong positive correlation was found between the change of oscillation power and the change in the number of infected cases, which was consistent with the simulation results using a conceptual hybrid model. The establishment of reliable and effective analytical methods contributes to a better understanding of infectious diseases’ oscillation cycle characteristics. Our research has certain guiding significance for the effective prevention and control of class B infectious diseases.

Prevention schemes for future pandemic cases: mathematical model and experience of interurban multi-agent COVID-19 epidemic prevention

To enhance the effectiveness of epidemic prevention (EP) in urban sustainability transformation, joint prevention and control mechanism should be established to prevent and control the COVID-19 epidemic. The interurban multi-agent EP strategy, as a key component of this mechanism, includes the spontaneous EP model, the superior leading EP model, and the collaborative EP model. In this study, firstly, the theoretical mechanism of the interurban multi-agent EP strategy was analyzed. Then, we proposed a three-party differential game model including factors such as the risk coefficient for the virus infection and EP experience teaching. Finally, prevention strategies, prevention efficiency, and prevention losses were compared under the three models based on theoretical analysis and numerical analysis. The results of this study are as follows. COVID-19 EP should be guided by a model of central government (CG) leadership, interurban collaboration, and social participation. The CG and urban governments (UGs) should comprehensively carry out COVID-19 EP from various aspects, including EP experience teaching, mass EP comfort, the utilization rate of EP funds, and the ability to implement strategies. During the course of the COVID-19 EP, when the CG and UGs transition from spontaneous EP model to a higher-level EP model, the UG's EP efforts will be enhanced. Under the collaborative EP model, the CG and UGs undergo the highest levels of EP effort. Compared with spontaneous EP model, the superior leading EP model can promote a Pareto improvement for all parties. From the perspective of total loss, the collaborative EP model is superior to the other two EP models. This study not only provides practical guidance for coordinating interurban relationships and enabling multi-agents to fully form joint forces, but also provides theoretical support for the establishment of an interurban joint EP mechanism under unified leadership.

Using the IPcase Index with Inflection Points and the Corresponding Case Numbers to Identify the Impact Hit by COVID-19 in China: An Observation Study

Coronavirus disease 2019 (COVID-19) occurred in Wuhan and rapidly spread around the world. Assessing the impact of COVID-19 is the first and foremost concern. The inflection point (IP) and the corresponding cumulative number of infected cases (CNICs) are the two viewpoints that should be jointly considered to differentiate the impact of struggling to fight against COVID-19 (SACOVID). The CNIC data were downloaded from the GitHub website on 23 November 2020. The item response theory model (IRT) was proposed to draw the ogive curve for every province/metropolitan city/area in China. The ipcase-index was determined by multiplying the IP days with the corresponding CNICs. The IRT model was parameterized, and the IP days were determined using the absolute advantage coefficient (AAC). The difference in SACOVID was compared using a forest plot. In the observation study, the top three regions hit severely by COVID-19 were Hong Kong, Shanghai, and Hubei, with IPcase indices of 1744, 723, and 698, respectively, and the top three areas with the most aberrant patterns were Yunnan, Sichuan, and Tianjin, with IP days of 5, 51, and 119, respectively. The difference in IP days was determined (χ2 = 5065666, df = 32, p < 0.001) among areas in China. The IRT model with the AAC is recommended to determine the IP days during the COVID-19 pandemic.

Mathematical model of COVID-19 with comorbidity and controlling using non-pharmaceutical interventions and vaccination

Pandemic is an unprecedented public health situation, especially for human beings with comorbidity. Vaccination and non-pharmaceutical interventions only remain extensive measures carrying a significant socioeconomic impact to defeating pandemic. Here, we formulate a mathematical model with comorbidity to study the transmission dynamics as well as an optimal control-based framework to diminish COVID-19. This encompasses modeling the dynamics of invaded population, parameter estimation of the model, study of qualitative dynamics, and optimal control problem for non-pharmaceutical interventions (NPIs) and vaccination events such that the cost of the combined measure is minimized. The investigation reveals that disease persists with the increase in exposed individuals having comorbidity in society. The extensive computational efforts show that mean fluctuations in the force of infection increase with corresponding entropy. This is a piece of evidence that the outbreak has reached a significant portion of the population. However, optimal control strategies with combined measures provide an assurance of effectively protecting our population from COVID-19 by minimizing social and economic costs.

Prevention schemes for future pandemic cases: mathematical model and experience of interurban multi-agent COVID-19 epidemic prevention

To enhance the effectiveness of epidemic prevention (EP) in urban sustainability transformation, joint prevention and control mechanism should be established to prevent and control the COVID-19 epidemic. The interurban multi-agent EP strategy, as a key component of this mechanism, includes the spontaneous EP model, the superior leading EP model, and the collaborative EP model. In this study, firstly, the theoretical mechanism of the interurban multi-agent EP strategy was analyzed. Then, we proposed a three-party differential game model including factors such as the risk coefficient for the virus infection and EP experience teaching. Finally, prevention strategies, prevention efficiency, and prevention losses were compared under the three models based on theoretical analysis and numerical analysis. The results of this study are as follows. COVID-19 EP should be guided by a model of central government (CG) leadership, interurban collaboration, and social participation. The CG and urban governments (UGs) should comprehensively carry out COVID-19 EP from various aspects, including EP experience teaching, mass EP comfort, the utilization rate of EP funds, and the ability to implement strategies. During the course of the COVID-19 EP, when the CG and UGs transition from spontaneous EP model to a higher-level EP model, the UG's EP efforts will be enhanced. Under the collaborative EP model, the CG and UGs undergo the highest levels of EP effort. Compared with spontaneous EP model, the superior leading EP model can promote a Pareto improvement for all parties. From the perspective of total loss, the collaborative EP model is superior to the other two EP models. This study not only provides practical guidance for coordinating interurban relationships and enabling multi-agents to fully form joint forces, but also provides theoretical support for the establishment of an interurban joint EP mechanism under unified leadership.

Mechanisms of recurrent outbreak of COVID-19: a model-based study

Recurrent outbreaks of the coronavirus disease 2019 (COVID-19) have occurred in many countries around the world. We developed a twofold framework in this study, which is composed by one novel descriptive model to depict the recurrent global outbreaks of COVID-19 and one dynamic model to understand the intrinsic mechanisms of recurrent outbreaks. We used publicly available data of cumulative infected cases from 1 January 2020 to 2 January 2021 in 30 provinces in China and 43 other countries around the world for model validation and further analyses. These time series data could be well fitted by the new descriptive model. Through this quantitative approach, we discovered two main mechanisms that strongly correlate with the extent of the recurrent outbreak: the sudden increase in cases imported from overseas and the relaxation of local government epidemic prevention policies. The compartmental dynamical model (Susceptible, Exposed, Infectious, Dead and Recovered (SEIDR) Model) could reproduce the obvious recurrent outbreak of the epidemics and showed that both imported infected cases and the relaxation of government policies have a causal effect on the emergence of a new wave of outbreak, along with variations in the temperature index. Meanwhile, recurrent outbreaks affect consumer confidence and have a significant influence on GDP. These results support the necessity of policies such as travel bans, testing of people upon entry, and consistency of government prevention and control policies in avoiding future waves of epidemics and protecting economy.

A fractional order HIV-TB co-infection model in the presence of exogenous reinfection and recurrent TB

In this article, a novel fractional order model has been introduced in Caputo sense for HIV-TB co-infection in the presence of exogenous reinfection and recurrent TB along with the treatment for both HIV and TB. The main aim of considering the fractional order model is to incorporate the memory effect of both diseases. We have analyzed both sub-models separately with fractional order. The basic reproduction number, which measures the contagiousness of the disease, is determined. The HIV sub-model is shown to have a locally asymptotically stable disease-free equilibrium point when the corresponding reproduction number, R H , is less than unity, whereas, for R H > 1 , the endemic equilibrium point comes into existence. For the TB sub-model, the disease-free equilibrium point has been proved to be locally asymptotically stable for R T < 1 . The existence of TB endemic equilibrium points in the presence of reinfection and recurrent TB for R T < 1 justifies the existence of backward bifurcation under certain restrictions on the parameters. Further, we numerically simulate the fractional order model to verify the analytical results and highlight the role of fractional order in co-infection modeling. The fractional order derivative is shown to have a crucial role in determining the transmission dynamics of HIV-TB co-infection. It is concluded that the memory effect plays a significant role in reducing the infection prevalence of HIV-TB co-infection. An increment in the number of recovered individuals can also be observed when the memory effect is taken into consideration by introducing fractional order model.